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Microscaled modeling of laboratory experiments, which needs adaptation a number of parameters of numerical model of a composite kern building, uses for the applying results of flowing laboratory experiments in sector and full hydrodynamic models of occurrences. Adaptation of parameters of numerical kern model shall be carried out at reproduction measured variables of flowing experiments. Moreover, there are uncertainties of filtration and capacitance properties related to heterogeneity of kern samples and instability of heated polymer’ displacement front. Iteration algorithm is developed and implemented in this article. Algorithm provides adapting of series synthetic hydrodynamic models of laboratory experiments. At the first adapting step the whole range of uncertainties of a series of laboratory experiments is taken into account. Minimization of number of variable parameters and model’ adaptation error realizes on all iteration steps. To increase the reliability of adaptation, the spectrum of 1D models is supplements with synthetic 3D models with stochastic distribution of heterogeneity in porosity and permeability. This process allows take processes of filtration in polymer adsorption conditions and heterogeneity of collector properties into account more fully while modeling. In addition, it can help to specify variable parameters with scaling on different numerical grids. Developed algorithm tested on heated polymer’ displacement experiments, determination of the relative phase permeability as a function of temperature. Decreased uncertainties of variable parameters, which are relative phase permeability as a function of concentration of polymer solution, residual resistance factor, dependence of the viscosity of the polymer solution on the shear rate, is the results of method’s application. Then these results transfers to the adaptation process of sector and full hydrodynamic models.
Microscaled modeling of laboratory experiments, which needs adaptation a number of parameters of numerical model of a composite kern building, uses for the applying results of flowing laboratory experiments in sector and full hydrodynamic models of occurrences. Adaptation of parameters of numerical kern model shall be carried out at reproduction measured variables of flowing experiments. Moreover, there are uncertainties of filtration and capacitance properties related to heterogeneity of kern samples and instability of heated polymer’ displacement front. Iteration algorithm is developed and implemented in this article. Algorithm provides adapting of series synthetic hydrodynamic models of laboratory experiments. At the first adapting step the whole range of uncertainties of a series of laboratory experiments is taken into account. Minimization of number of variable parameters and model’ adaptation error realizes on all iteration steps. To increase the reliability of adaptation, the spectrum of 1D models is supplements with synthetic 3D models with stochastic distribution of heterogeneity in porosity and permeability. This process allows take processes of filtration in polymer adsorption conditions and heterogeneity of collector properties into account more fully while modeling. In addition, it can help to specify variable parameters with scaling on different numerical grids. Developed algorithm tested on heated polymer’ displacement experiments, determination of the relative phase permeability as a function of temperature. Decreased uncertainties of variable parameters, which are relative phase permeability as a function of concentration of polymer solution, residual resistance factor, dependence of the viscosity of the polymer solution on the shear rate, is the results of method’s application. Then these results transfers to the adaptation process of sector and full hydrodynamic models.
The article describes the results of research about the creation of an empirical method for calculation relative phase permeability functions (RPP). The method based on calculation of interfacial interaction function (IIF) from the experimental SCAL data and searching multi-parameter dependences for the parameters of the approximation dependence of IIF. It is proposed to use a function defined on two segments of the domain of definition, for approximation of IIF. The research had been carried out on laboratory data for group of terrigenous and carbonate samples. It had been established that the pressure losses due to interfacial interaction of oil and water during the joint flow of the water-oil mixture are at the maximum for the considered core samples from 60 to 90% of the total pressure losses. Multi-parameter dependences for IIF parameters were found for both groups of data. It was defined that using of multi-parameter dependences for IIF parameters provides the quality of RPP forecast with deviation by 30% for terrigenous samples and by 22% for carbonate samples. There was conducted the study of the influence of data set amount for multi-parameter dependences (training set) on the quality of RPP forecast (test set). It had been established that increasing of data set amount for multi-parameter dependences of IIF parameters has a positive effect on the quality of RPP functions forecast. At the same time, the increasing of data set amount in 2 times leads to decreasing of the average relative error of RPP calculation from 25.5 to 20.9% for terrigenous samples and from 70.3 to 23.6% for carbonate samples.
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